Offline verification with document filter

ABSTRACT

An example operation may include one or more of obtaining a machine-readable code from a first document among a set of documents, extracting a probabilistic data structure from the machine-readable code which includes probabilistic hashes accumulated from the set of documents, determining whether a document hash of a second document is included within the probabilistic data structure, and in response to a determination that the document hash is included within the probabilistic data structure, outputting a notification indicating the second document is included in the set of documents.

TECHNICAL FIELD

This application generally relates to a system for storing data via ablockchain, and more particularly, to a process of verifying a block ispart of a sequence of blocks and its order in the sequence using aprobabilistic filter such as a Bloom filter.

BACKGROUND

A centralized database stores and maintains data in a single database(e.g., a database server) at one location. This location is often acentral computer, for example, a desktop central processing unit (CPU),a server CPU, or a mainframe computer. Information stored on acentralized database is typically accessible from multiple differentpoints. Multiple users or client workstations can work simultaneously onthe centralized database, for example, based on a client/serverconfiguration. A centralized database is easy to manage, maintain, andcontrol, especially for purposes of security because of its singlelocation. Within a centralized database, data redundancy is minimized asa single storing place of all data also implies that a given set of dataonly has one primary record.

Recently, organizations have been turning to blockchain as an improvedstorage system over a traditional database. Blockchain offers numerousbenefits over a traditional database including data redundancy, nocentral authority, multiple nodes of access, and the like. Anotherbenefit of blockchain is its immutability. In particular, each new blockincludes a hash of a previous block in the chain which creates animmutable chain of blocks. However, in order to verify that an olderblock is part of the chain using a more recent block, a hashverification of all blocks in sequence between more recent block and theolder block must be performed. A ledger may store hundreds, thousands,or even more blocks. Therefore, this verification process may requirehundreds or thousands of hash verifications. As such, what is needed isa solution that improves and overcomes these drawbacks and limitations.

SUMMARY

One example embodiment provides an apparatus that includes one or moreof a storage configured to store a data block that is included within asequential chain of data blocks and which comprises a probabilistic datastructure stored therein, and a processor configured to one or more ofreceive a request to verify another data block, determine whether aprobabilistic hash of the other data block is included within theprobabilistic data structure of the stored data block, and in responseto a determination that the hash of the other data block is includedwithin the probabilistic data structure, store an indicator that theother data block is included within the sequential chain of data blocks.

Another example embodiment provides a method that includes one or moreof storing a data block that is included within a sequential chain ofdata blocks and which comprises a probabilistic data structure storedtherein, receiving a request to verify another data block, determiningwhether a probabilistic hash of the other data block is included withinthe probabilistic data structure of the stored data block, and inresponse to a determination that the hash of the other data block isincluded within the probabilistic data structure, storing an indicatorthat the other data block is included within the sequential chain ofdata blocks.

A further example embodiment provides a method that includes one or moreof storing a data block that is included within a sequential chain ofdata blocks and which comprises a probabilistic data structure storedtherein, receiving a request to verify a transaction is included in thedata block, determining whether a probabilistic hash of the transactionis included within the probabilistic data structure of the data block,and in response to a determination that the probabilistic hash of thetransaction is included within the probabilistic data structure of thedata block, storing an indicator that the transaction is included withinthe data block.

Another example embodiment provides an apparatus that includes one ormore of a processor configured to one or more of obtain amachine-readable code from a first document among a set of documents,extract a probabilistic data structure from the machine-readable codewhich includes probabilistic hashes accumulated from the set ofdocuments, and determine whether a document hash of a second document isincluded within the probabilistic data structure, and a displayconfigured to output a notification that indicates the second documentis included in the set of documents, in response to a determination thatthe document hash is included within the probabilistic data structure.

A further example embodiment provides a method that includes one or moreof obtaining a machine-readable code from a first document among a setof documents, extracting a probabilistic data structure from themachine-readable code which includes probabilistic hashes accumulatedfrom the set of documents, determining whether a document hash of asecond document is included within the probabilistic data structure, andin response to a determination that the document hash is included withinthe probabilistic data structure, outputting a notification indicatingthe second document is included in the set of documents.

A further example embodiment provides a non-transitory computer-readablemedium comprising instructions, that when read by a processor, cause theprocessor to perform a method that includes one or more of obtaining amachine-readable code from a first document among a set of documents,extracting a probabilistic data structure from the machine-readable codewhich includes probabilistic hashes accumulated from the set ofdocuments, determining whether a document hash of a second document isincluded within the probabilistic data structure, and in response to adetermination that the document hash is included within theprobabilistic data structure, outputting a notification indicating thesecond document is included in the set of documents.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A is a diagram illustrating a blockchain system for one-step hashverification of a block and block content according to exampleembodiments.

FIG. 1B is a diagram illustrating process for one-step hash verificationof a document according to example embodiments.

FIG. 2A is a diagram illustrating an example blockchain architectureconfiguration, according to example embodiments.

FIG. 2B is a diagram illustrating a blockchain transactional flow amongnodes, according to example embodiments.

FIG. 3A is a diagram illustrating a permissioned network, according toexample embodiments.

FIG. 3B is a diagram illustrating another permissioned network,according to example embodiments.

FIG. 3C is a diagram illustrating a permissionless network, according toexample embodiments.

FIG. 4A is a diagram illustrating a process of generating a probabilityfilter for data blocks in a blockchain according to example embodiments.

FIG. 4B is a diagram illustrating a process of verifying a previousblock based on a probabilistic filter according to example embodiments.

FIG. 4C is a diagram illustrating a process of a generating aprobability filter for transactions in a block according to exampleembodiments.

FIG. 4D is a diagram illustrating a process of verifying a documentbased on a probabilistic filter according to example embodiments.

FIG. 5A is a diagram illustrating a method of verifying a block isincluded in a sequence of blocks according to example embodiments.

FIG. 5B is a diagram illustrating a method of verifying a transaction isincluded in a block according to example embodiments.

FIG. 5C is a diagram illustrating a method of verifying a document islinked to another document according to example embodiments.

FIG. 6A is a diagram illustrating an example system configured toperform one or more operations described herein, according to exampleembodiments.

FIG. 6B is a diagram illustrating another example system configured toperform one or more operations described herein, according to exampleembodiments.

FIG. 6C is a diagram illustrating a further example system configured toutilize a smart contract, according to example embodiments.

FIG. 6D is a diagram illustrating yet another example system configuredto utilize a blockchain, according to example embodiments.

FIG. 7A is a diagram illustrating a process of a new block being addedto a distributed ledger, according to example embodiments.

FIG. 7B is a diagram illustrating data contents of a new data block,according to example embodiments.

FIG. 7C is a diagram illustrating a blockchain for digital content,according to example embodiments.

FIG. 7D is a diagram illustrating a block which may represent thestructure of blocks in the blockchain, according to example embodiments.

FIG. 8A is a diagram illustrating an example blockchain which storesmachine learning (artificial intelligence) data, according to exampleembodiments.

FIG. 8B is a diagram illustrating an example quantum-secure blockchain,according to example embodiments.

FIG. 9 is a diagram illustrating an example system that supports one ormore of the example embodiments.

DETAILED DESCRIPTION

It will be readily understood that the instant components, as generallydescribed and illustrated in the figures herein, may be arranged anddesigned in a wide variety of different configurations. Thus, thefollowing detailed description of the embodiments of at least one of amethod, apparatus, non-transitory computer readable medium and system,as represented in the attached figures, is not intended to limit thescope of the application as claimed but is merely representative ofselected embodiments.

The instant features, structures, or characteristics as describedthroughout this specification may be combined or removed in any suitablemanner in one or more embodiments. For example, the usage of the phrases“example embodiments”, “some embodiments”, or other similar language,throughout this specification refers to the fact that a particularfeature, structure, or characteristic described in connection with theembodiment may be included in at least one embodiment. Thus, appearancesof the phrases “example embodiments”, “in some embodiments”, “in otherembodiments”, or other similar language, throughout this specificationdo not necessarily all refer to the same group of embodiments, and thedescribed features, structures, or characteristics may be combined orremoved in any suitable manner in one or more embodiments. Further, inthe diagrams, any connection between elements can permit one-way and/ortwo-way communication even if the depicted connection is a one-way ortwo-way arrow. Also, any device depicted in the drawings can be adifferent device. For example, if a mobile device is shown sendinginformation, a wired device could also be used to send the information.

In addition, while the term “message” may have been used in thedescription of embodiments, the application may be applied to many typesof networks and data. Furthermore, while certain types of connections,messages, and signaling may be depicted in exemplary embodiments, theapplication is not limited to a certain type of connection, message, andsignaling.

Example embodiments provide methods, systems, components, non-transitorycomputer readable media, devices, and/or networks, which provideprobabilistic verification of sequential data. For example, a block canbe verified as being part of a chain of blocks using a one-stepverification. As another example, a document can be verified as beingpart of a group of documents using a one-step verification.

In one embodiment the system deploys and configures a decentralizeddatabase (such as a blockchain) that is a distributed storage system,which includes multiple nodes that communicate with each other. Thedecentralized database includes an append-only immutable data structureresembling a distributed ledger capable of maintaining records betweenmutually untrusted parties. The untrusted parties are referred to hereinas peers or peer nodes. Each peer maintains a copy of the databaserecords and no single peer can modify the database records without aconsensus being reached among the distributed peers. For example, thepeers may execute a consensus protocol to validate blockchain storagetransactions, group the storage transactions into blocks, and build ahash chain over the blocks. This process forms the ledger by orderingthe storage transactions, as is necessary, for consistency. In variousembodiments, a permissioned and/or a permissionless blockchain can beused. In a public or permission-less blockchain, anyone can participatewithout a specific identity. Public blockchains can involve nativecryptocurrency and use consensus based on various protocols such asProof of Work (PoW). On the other hand, a permissioned blockchaindatabase provides secure interactions among a group of entities whichshare a common goal but which do not fully trust one another, such asbusinesses that exchange funds, goods, information, and the like.

The blockchain may operate arbitrary, programmable logic, tailored to adecentralized storage scheme and referred to as “smart contracts” or“chaincodes.” In some cases, specialized chaincodes may exist formanagement functions and parameters which are referred to as systemchaincode. The application can further utilize smart contracts that aretrusted distributed applications which leverage tamper-proof propertiesof the blockchain database and an underlying agreement between nodes,which is referred to as an endorsement or endorsement policy. Blockchaintransactions associated with this application can be “endorsed” beforebeing committed to the blockchain while transactions, which are notendorsed, are disregarded. An endorsement policy allows chaincode tospecify endorsers for a transaction in the form of a set of peer nodesthat are necessary for endorsement. When a client sends the transactionto the peers specified in the endorsement policy, the transaction isexecuted to validate the transaction. After validation, the transactionsenter an ordering phase in which a consensus protocol is used to producean ordered sequence of endorsed transactions grouped into blocks.

The blockchain can include nodes configured therein that are thecommunication entities of the blockchain system. A “node” may perform alogical function in the sense that multiple nodes of different types canrun on the same physical server. Nodes are grouped in trust domains andare associated with logical entities that control them in various ways.Nodes may include different types, such as a client or submitting-clientnode which submits a transaction-invocation to an endorser (e.g., peer),and broadcasts transaction-proposals to an ordering service (e.g.,ordering node). Another type of node is a peer node which can receiveclient submitted transactions, commit the transactions and maintain astate and a copy of the ledger of blockchain transactions. Peers canalso have the role of an endorser, although it is not a requirement. Anordering-service-node or orderer is a node running the communicationservice for all nodes, and which implements a delivery guarantee, suchas a broadcast to each of the peer nodes in the system when committingtransactions and modifying a world state of the blockchain, which isanother name for the initial blockchain transaction which normallyincludes control and setup information.

The blockchain may include a ledger that is a sequenced,tamper-resistant record of all state transitions of a blockchain. Statetransitions may result from chaincode invocations (i.e., transactions)submitted by participating parties (e.g., client nodes, ordering nodes,endorser nodes, peer nodes, etc.). Each participating party (such as apeer node) can maintain a copy of the ledger. A transaction may resultin a set of asset key-value pairs being committed to the ledger as oneor more operands, such as creates, updates, deletes, and the like. Theledger includes a blockchain (also referred to as a chain) which is usedto store an immutable, sequenced record in blocks. The ledger alsoincludes a state database which maintains a current state of theblockchain.

The chain (of the blockchain) is a transaction log which is structuredas hash-linked blocks, and each block contains a sequence of Ntransactions where N is equal to or greater than one. The block headerincludes a hash of the block's transactions, as well as a hash of theprior block's header. In this way, all transactions on the ledger may besequenced and cryptographically linked together. Accordingly, it is notpossible to tamper with the ledger data without breaking the hash links.A hash of a most recently added blockchain block represents everytransaction on the chain that has come before it, making it possible toensure that all peer nodes are in a consistent and trusted state. Thechain may be stored on a peer node file system (i.e., local, attachedstorage, cloud, etc.), efficiently supporting the append-only nature ofthe blockchain workload.

The current state of the immutable ledger represents the latest valuesfor all keys that are included in the chain transaction log. Since thecurrent state represents the latest key values known to a channel, it issometimes referred to as a world state. Chaincode invocations executetransactions against the current state data of the ledger. To make thesechaincode interactions efficient, the latest values of the keys may bestored in a state database. The state database may be simply an indexedview into the chain's transaction log, it can therefore be regeneratedfrom the chain at any time. The state database may automatically berecovered (or generated if needed) upon peer node startup, and beforetransactions are accepted.

A traditional data block of a blockchain stores a hash of a previousblock in the chain. This sequence of hashes creates an immutable chainwhere each block can be used to recover any other block on the chain.However, in order to verify that a previous block (e.g., block 25) ispart of same chain as a newer block (e.g., block 75), a hashverification must be performed on each block between the newer block andthe previous block. In this example, fifty hash verifications would needto be performed and in a sequential order requiring block 74 to beverified before block 73, and so on.

To address this issue, an example embodiment provides for a one-stepverification process of a data block based on an accumulative filter(probabilistic filter) that may be stored within a data block. Theprobabilistic filter may store a set of probabilistic hashes of allblocks in the chain within a compacted data structure (e.g., a Bloomfilter, etc.). For example, the probabilistic data structure may includea bit array. Each block includes a probabilistic filter that includesthe hash values stored in the probabilistic filter of the previous blockplus a hash value of the previous block accumulated therein. In otherwords, the probabilistic filter accumulates more probabilistic hashvalues as new blocks are added. However, the size of the probabilisticfilter remains the same.

When a system needs to verify that a previous block (e.g., block 25) isincluded in the same chain as a newer block (e.g., block 75), the systemcan retrieve a probabilistic filter from the newer block and perform aone-step verification process to verify that a hash of the previousblock is included in the probabilistic filter. That is, the system canuse a probabilistic filter stored in a new block to verify that anon-consecutive previous block is also stored on the chain with aone-step hash verification. Therefore, the system can verify that block25 has a hash value represented by the probabilistic filter stored inblock 75 (which is a non-consecutive block). Because the probabilisticdata structure uses a compacted representation of a block, there is asmall margin for error. However, the greater the size of theprobabilistic data structure the less chance of error. In someembodiments, the probabilistic data structure can be hashed to furthercompact its size.

In the examples herein, the inclusion of the probabilistic filter withina data block may be used to determine the relative order of blocks, forexample, which block was created before the other when comparing twoblocks. This is important for permissioned blockchains based onsignature mining (e.g., determining when a block is created by signingits content by authorized parties, etc.)

As another example, a probabilistic data structure may store aprobabilistic hash of all transactions in a data block. In this example,a probabilistic hash may be performed for each transaction (or hashthereof) and may be stored in the probabilistic data structure.Therefore, a user or system can verify that a transaction is part of theblock based on a verification using the probabilistic data structure.

In another embodiments, the probabilistic data structure can be used toperform an offline verification of document content such as contracts,digital documents, receipts, invoices, and the like. In this example,the probabilistic data structure may include a hash of all previousdocuments in a group, and the probabilistic data structure may beembedded within a code (e.g., a quick response code) that can be addedto a most recent document in the group. A user may scan the QR code(e.g., with a mobile application, etc.) and read the probabilistic datastructure from the newer document. The user may also scan a QR code of aprevious document to obtain a hash value of the previous document. Thesystem may verify that the hash of the previous document is included inthe probabilistic data structure. In response to a successfulverification, the system knows that the two documents are from the sameset. In addition, the system knows that the previous document came priorto the most recent document.

The verification of blocks and transaction content is essential to theoperation of a blockchain. However, the amount of processing timenecessary to verify that a block is part of a blockchain (which mayinclude thousands of blocks or more) can require thousands of hashverifications or more. In contrast, the probabilistic hash verificationprocess herein can perform a one-step verification (one hashverification) to determine whether a block is included within a largergroup of linked blocks. Some of the benefits of this system includeconservation of processing resources and computational cost whileenabling fast verifications to be performed. Another benefit of theexample embodiments is the ability to verify that two documents arerelated, and also verify that one document precedes another document.This can be important for time-sensitive documents such as contracts,and the like.

FIG. 1A illustrates a blockchain system 100 for one-step hashverification of a block and block content according to exampleembodiments. Referring to FIG. 1, the system 100 includes a group ofblockchain peer nodes 121-124 which share a distributed ledger includinga blockchain 120. Clients (e.g., client 110, etc.) may submittransactions which are processed by the blockchain peer nodes 121-124and then stored in a data block through orderer node 125. The data blockmay then be committed to the blockchain 120 stored by each of theblockchain peer nodes 121-124.

As a non-limiting example, the client 110 may desire to verify that apreviously stored transaction/document is a document that has beenapproved and stored on the blockchain 120. In this example, the client110 may be satisfied if the client 110 can verify that the document isstored in a valid block of the blockchain 120. The client 110 mayprovide the blockchain network (e.g., peer node 121) with an identifierof a block or transaction of the document in question. In response, thepeer node 121 may perform a one-step verification to verify that thedocument is stored in a valid block on the blockchain 120.

For example, the peer node 121 may retrieve a most recently stored block(or some other block that the peer node 121 trusts). A probabilisticdata structure such as a Bloom filter, a Cuckoo filter, etc., may bestored in the block and may include a probabilistic hash of all previousblocks on the chain. The peer node 121 may retrieve a block identifiedby the client 110 as including the document in question. Here, the peernode 121 may retrieve the hash of the block, and create a probabilistichash of the block hash. Next, the peer node 121 may verify whether theprobabilistic hash of the block in question is included within theprobabilistic filter stored in the most recent/trusted block, and outputthe results to the client 110.

As further described herein with respect to FIGS. 4A-4D, a probabilisticdata structure (e.g., a Bloom filter, etc.) may include a bit array withan index identifying each cell in the array as shown below:

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14

Here, each empty cell in the array represents a bit, and the numberbelow is its index. To add an element (such as a block hash) to theprobabilistic data structure, the block hash may be hashed one or moretimes using a probabilistic hash function which results in a few bitvalues. To represent the probabilistic hash of the block hash, the bitvalues in the array shown above may be set to “1” while bit values thatare blank or “0” represent values that are not in the set. For example,below is the result of a probabilistic hash of the string“xyzabcdefghi123456789.”

1 1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14

As can be seen, the string is converted into a much smaller size bitvalue with a one value being stored at index=2 and index=8. To test if ablock hash is included in the probabilistic data structure describedherein, a peer node or other entity may hash the block hash using aprobabilistic hash function and verify whether the resulting bit valuesare stored in the probabilistic hash structure of a current block ortrusted block. If the values are stored in the probabilistic hashstructure, there is a good chance that the block is part of the chain.However, if one or more of the values are not stored in theprobabilistic hash structure, the block is not part of the chain. Therewill be small margin of error since the probabilistic data structurecompresses the hash data into smaller form. However, the larger the bitarray used (versus the number of blocks in the chain) can be modified toimprove the error margin.

In some embodiments, an orderer node 125 may generate the probabilisticfilter and store it in a block, when creating the block. Here, theorderer node 125 may receive transactions which have beenendorsed/approved, and build a data block based on the transactions. Inaddition, the order node 125 may generate a probabilistic data structureincluding the probabilistic hashes of the block hashes of all previousblocks on the ledger.

FIG. 1B illustrates a process 130 for one-step hash verification of adocument according to example embodiments. Here, a user device 160 mayscan a QR code and extract information therefrom to determine whetherdocuments are linked to each other. In this example, the user device 160does not need to be connected to a backend network or blockchain.Therefore, the process 130 may be performed offline.

In this example, the user device 160 may be a mobile device having amobile application installed therein capable of performing ascan/verification process. Here, a user is attempting to verify that anold document 140 is linked to a new document 150. The user device 160may scan a QR code 152 from the new document 150, and extract aprobabilistic data structure embedded in the QR code 152. Meanwhile, theuser device 160 may also scan a QR code 142 from the old document 140and extract a hash of the old document 140 from the QR code 142. Then,the user device may verify that a probabilistic hash of the hash of theold document 140 is included in the probabilistic data structureembedded in the QR code 152. If the hash of the old document 140 isincluded therein, the user device 160 can determine that the twodocuments are linked, and that the old document 140 is prior in timethan the new document 150. That is, because the new document 150includes a probabilistic data structure with a hash of the old document,it can be inferred that the old document 140 is previous in the chain tothe new document 150.

FIG. 2A illustrates a blockchain architecture configuration 200,according to example embodiments. Referring to FIG. 2A, the blockchainarchitecture 200 may include certain blockchain elements, for example, agroup of blockchain nodes 202. The blockchain nodes 202 may include oneor more nodes 204-210 (these four nodes are depicted by example only).These nodes participate in a number of activities, such as blockchaintransaction addition and validation process (consensus). One or more ofthe blockchain nodes 204-210 may endorse transactions based onendorsement policy and may provide an ordering service for allblockchain nodes in the architecture 200. A blockchain node may initiatea blockchain authentication and seek to write to a blockchain immutableledger stored in blockchain layer 216, a copy of which may also bestored on the underpinning physical infrastructure 214. The blockchainconfiguration may include one or more applications 224 which are linkedto application programming interfaces (APIs) 222 to access and executestored program/application code 220 (e.g., chaincode, smart contracts,etc.) which can be created according to a customized configurationsought by participants and can maintain their own state, control theirown assets, and receive external information. This can be deployed as atransaction and installed, via appending to the distributed ledger, onall blockchain nodes 204-210.

The blockchain base or platform 212 may include various layers ofblockchain data, services (e.g., cryptographic trust services, virtualexecution environment, etc.), and underpinning physical computerinfrastructure that may be used to receive and store new transactionsand provide access to auditors which are seeking to access data entries.The blockchain layer 216 may expose an interface that provides access tothe virtual execution environment necessary to process the program codeand engage the physical infrastructure 214. Cryptographic trust services218 may be used to verify transactions such as asset exchangetransactions and keep information private.

The blockchain architecture configuration of FIG. 2A may process andexecute program/application code 220 via one or more interfaces exposed,and services provided, by blockchain platform 212. The code 220 maycontrol blockchain assets. For example, the code 220 can store andtransfer data, and may be executed by nodes 204-210 in the form of asmart contract and associated chaincode with conditions or other codeelements subject to its execution. As a non-limiting example, smartcontracts may be created to execute reminders, updates, and/or othernotifications subject to the changes, updates, etc. The smart contractscan themselves be used to identify rules associated with authorizationand access requirements and usage of the ledger. For example, a read set226 may be processed by one or more processing entities (e.g., virtualmachines) included in the blockchain layer 216. A write set 228 mayinclude a result of processing the read set 226 via one or more smartcontracts. The physical infrastructure 214 may be utilized to retrieveany of the data or information described herein.

A smart contract may be created via a high-level application andprogramming language, and then written to a block in the blockchain. Thesmart contract may include executable code which is registered, stored,and/or replicated with a blockchain (e.g., distributed network ofblockchain peers). A transaction is an execution of the smart contractcode which can be performed in response to conditions associated withthe smart contract being satisfied. The executing of the smart contractmay trigger a trusted modification(s) to a state of a digital blockchainledger. The modification(s) to the blockchain ledger caused by the smartcontract execution may be automatically replicated throughout thedistributed network of blockchain peers through one or more consensusprotocols.

The smart contract may write data to the blockchain in the format ofkey-value pairs. Furthermore, the smart contract code can read thevalues stored in a blockchain and use them in application operations.The smart contract code can write the output of various logic operationsinto the blockchain. The code may be used to create a temporary datastructure in a virtual machine or other computing platform. Data writtento the blockchain can be public and/or can be encrypted and maintainedas private. The temporary data that is used/generated by the smartcontract is held in memory by the supplied execution environment, thendeleted once the data needed for the blockchain is identified.

A chaincode may include the code interpretation of a smart contract,with additional features. As described herein, the chaincode may beprogram code deployed on a computing network, where it is executed andvalidated by chain validators together during a consensus process. Thechaincode receives a hash and retrieves from the blockchain a hashassociated with the data template created by use of a previously storedfeature extractor. If the hashes of the hash identifier and the hashcreated from the stored identifier template data match, then thechaincode sends an authorization key to the requested service. Thechaincode may write to the blockchain data associated with thecryptographic details.

FIG. 2B illustrates an example of a blockchain transactional flow 250between nodes of the blockchain in accordance with an exampleembodiment. Referring to FIG. 2B, the transaction flow may include atransaction proposal 291 sent by an application client node 260 to anendorsing peer node 281. The endorsing peer 281 may verify the clientsignature and execute a chaincode function to initiate the transaction.The output may include the chaincode results, a set of key/valueversions that were read in the chaincode (read set), and the set ofkeys/values that were written in chaincode (write set). The proposalresponse 292 is sent back to the client 260 along with an endorsementsignature, if approved. The client 260 assembles the endorsements into atransaction payload 293 and broadcasts it to an ordering service node284. The ordering service node 284 then delivers ordered transactions asblocks to all peers 281-283 on a channel. Before committal to theblockchain, each peer 281-283 may validate the transaction. For example,the peers may check the endorsement policy to ensure that the correctallotment of the specified peers have signed the results andauthenticated the signatures against the transaction payload 293.

Referring again to FIG. 2B, the client node 260 initiates thetransaction 291 by constructing and sending a request to the peer node281, which is an endorser. The client 260 may include an applicationleveraging a supported software development kit (SDK), which utilizes anavailable API to generate a transaction proposal. The proposal is arequest to invoke a chaincode function so that data can be read and/orwritten to the ledger (i.e., write new key value pairs for the assets).The SDK may serve as a shim to package the transaction proposal into aproperly architected format (e.g., protocol buffer over a remoteprocedure call (RPC)) and take the client's cryptographic credentials toproduce a unique signature for the transaction proposal.

In response, the endorsing peer node 281 may verify (a) that thetransaction proposal is well formed, (b) the transaction has not beensubmitted already in the past (replay-attack protection), (c) thesignature is valid, and (d) that the submitter (client 260, in theexample) is properly authorized to perform the proposed operation onthat channel. The endorsing peer node 281 may take the transactionproposal inputs as arguments to the invoked chaincode function. Thechaincode is then executed against a current state database to producetransaction results including a response value, read set, and write set.However, no updates are made to the ledger at this point. In 292, theset of values, along with the endorsing peer node's 281 signature ispassed back as a proposal response 292 to the SDK of the client 260which parses the payload for the application to consume.

In response, the application of the client 260 inspects/verifies theendorsing peers signatures and compares the proposal responses todetermine if the proposal response is the same. If the chaincode onlyqueried the ledger, the application would inspect the query response andwould typically not submit the transaction to the ordering node service284. If the client application intends to submit the transaction to theordering node service 284 to update the ledger, the applicationdetermines if the specified endorsement policy has been fulfilled beforesubmitting (i.e., did all peer nodes necessary for the transactionendorse the transaction). Here, the client may include only one ofmultiple parties to the transaction. In this case, each client may havetheir own endorsing node, and each endorsing node will need to endorsethe transaction. The architecture is such that even if an applicationselects not to inspect responses or otherwise forwards an unendorsedtransaction, the endorsement policy will still be enforced by peers andupheld at the commit validation phase.

After successful inspection, in step 293 the client 260 assemblesendorsements into a transaction and broadcasts the transaction proposaland response within a transaction message to the ordering node 284. Thetransaction may contain the read/write sets, the endorsing peerssignatures and a channel ID. The ordering node 284 does not need toinspect the entire content of a transaction in order to perform itsoperation, instead the ordering node 284 may simply receive transactionsfrom all channels in the network, order them chronologically by channel,and create blocks of transactions per channel.

The blocks of the transaction are delivered from the ordering node 284to all peer nodes 281-283 on the channel. The transactions 294 withinthe block are validated to ensure any endorsement policy is fulfilledand to ensure that there have been no changes to ledger state for readset variables since the read set was generated by the transactionexecution. Transactions in the block are tagged as being valid orinvalid. Furthermore, in step 295 each peer node 281-283 appends theblock to the channel's chain, and for each valid transaction the writesets are committed to current state database. An event is emitted, tonotify the client application that the transaction (invocation) has beenimmutably appended to the chain, as well as to notify whether thetransaction was validated or invalidated.

FIG. 3A illustrates an example of a permissioned blockchain network 300,which features a distributed, decentralized peer-to-peer architecture.In this example, a blockchain user 302 may initiate a transaction to thepermissioned blockchain 304. In this example, the transaction can be adeploy, invoke, or query, and may be issued through a client-sideapplication leveraging an SDK, directly through an API, etc. Networksmay provide access to a regulator 306, such as an auditor. A blockchainnetwork operator 308 manages member permissions, such as enrolling theregulator 306 as an “auditor” and the blockchain user 302 as a “client”.An auditor could be restricted only to querying the ledger whereas aclient could be authorized to deploy, invoke, and query certain types ofchaincode.

A blockchain developer 310 can write chaincode and client-sideapplications. The blockchain developer 310 can deploy chaincode directlyto the network through an interface. To include credentials from atraditional data source 312 in chaincode, the developer 310 could use anout-of-band connection to access the data. In this example, theblockchain user 302 connects to the permissioned blockchain 304 througha peer node 314. Before proceeding with any transactions, the peer node314 retrieves the user's enrollment and transaction certificates from acertificate authority 316, which manages user roles and permissions. Insome cases, blockchain users must possess these digital certificates inorder to transact on the permissioned blockchain 304. Meanwhile, a userattempting to utilize chaincode may be required to verify theircredentials on the traditional data source 312. To confirm the user'sauthorization, chaincode can use an out-of-band connection to this datathrough a traditional processing platform 318.

FIG. 3B illustrates another example of a permissioned blockchain network320, which features a distributed, decentralized peer-to-peerarchitecture. In this example, a blockchain user 322 may submit atransaction to the permissioned blockchain 324. In this example, thetransaction can be a deploy, invoke, or query, and may be issued througha client-side application leveraging an SDK, directly through an API,etc. Networks may provide access to a regulator 326, such as an auditor.A blockchain network operator 328 manages member permissions, such asenrolling the regulator 326 as an “auditor” and the blockchain user 322as a “client”. An auditor could be restricted only to querying theledger whereas a client could be authorized to deploy, invoke, and querycertain types of chaincode.

A blockchain developer 330 writes chaincode and client-sideapplications. The blockchain developer 330 can deploy chaincode directlyto the network through an interface. To include credentials from atraditional data source 332 in chaincode, the developer 330 could use anout-of-band connection to access the data. In this example, theblockchain user 322 connects to the network through a peer node 334.Before proceeding with any transactions, the peer node 334 retrieves theuser's enrollment and transaction certificates from the certificateauthority 336. In some cases, blockchain users must possess thesedigital certificates in order to transact on the permissioned blockchain324. Meanwhile, a user attempting to utilize chaincode may be requiredto verify their credentials on the traditional data source 332. Toconfirm the user's authorization, chaincode can use an out-of-bandconnection to this data through a traditional processing platform 338.

In some embodiments, the blockchain herein may be a permissionlessblockchain. In contrast with permissioned blockchains which requirepermission to join, anyone can join a permissionless blockchain. Forexample, to join a permissionless blockchain a user may create apersonal address and begin interacting with the network, by submittingtransactions, and hence adding entries to the ledger. Additionally, allparties have the choice of running a node on the system and employingthe mining protocols to help verify transactions.

FIG. 3C illustrates a process 350 of a transaction being processed by apermissionless blockchain 352 including a plurality of nodes 354. Asender 356 desires to send payment or some other form of value (e.g., adeed, medical records, a contract, a good, a service, or any other assetthat can be encapsulated in a digital record) to a recipient 358 via thepermissionless blockchain 352. In one embodiment, each of the senderdevice 356 and the recipient device 358 may have digital wallets(associated with the blockchain 352) that provide user interfacecontrols and a display of transaction parameters. In response, thetransaction is broadcast throughout the blockchain 352 to the nodes 354.Depending on the blockchain's 352 network parameters the nodes verify360 the transaction based on rules (which may be pre-defined ordynamically allocated) established by the permissionless blockchain 352creators. For example, this may include verifying identities of theparties involved, etc. The transaction may be verified immediately or itmay be placed in a queue with other transactions and the nodes 354determine if the transactions are valid based on a set of network rules.

In structure 362, valid transactions are formed into a block and sealedwith a lock (hash). This process may be performed by mining nodes amongthe nodes 354. Mining nodes may utilize additional software specificallyfor mining and creating blocks for the permissionless blockchain 352.Each block may be identified by a hash (e.g., 256 bit number, etc.)created using an algorithm agreed upon by the network. Each block mayinclude a header, a pointer or reference to a hash of a previous block'sheader in the chain, and a group of valid transactions. The reference tothe previous block's hash is associated with the creation of the secureindependent chain of blocks.

Before blocks can be added to the blockchain, the blocks must bevalidated. Validation for the permissionless blockchain 352 may includea proof-of-work (PoW) which is a solution to a puzzle derived from theblock's header. Although not shown in the example of FIG. 3C, anotherprocess for validating a block is proof-of-stake. Unlike theproof-of-work, where the algorithm rewards miners who solve mathematicalproblems, with the proof of stake, a creator of a new block is chosen ina deterministic way, depending on its wealth, also defined as “stake.”Then, a similar proof is performed by the selected/chosen node.

With mining 364, nodes try to solve the block by making incrementalchanges to one variable until the solution satisfies a network-widetarget. This creates the PoW thereby ensuring correct answers. In otherwords, a potential solution must prove that computing resources weredrained in solving the problem. In some types of permissionlessblockchains, miners may be rewarded with value (e.g., coins, etc.) forcorrectly mining a block.

Here, the PoW process, alongside the chaining of blocks, makesmodifications of the blockchain extremely difficult, as an attacker mustmodify all subsequent blocks in order for the modifications of one blockto be accepted. Furthermore, as new blocks are mined, the difficulty ofmodifying a block increases, and the number of subsequent blocksincreases. With distribution 366, the successfully validated block isdistributed through the permissionless blockchain 352 and all nodes 354add the block to a majority chain which is the permissionlessblockchain's 352 auditable ledger. Furthermore, the value in thetransaction submitted by the sender 356 is deposited or otherwisetransferred to the digital wallet of the recipient device 358.

FIG. 4A illustrates a process 400 of generating a probability filter 422for data blocks in a blockchain 410 according to example embodiments.Referring to FIG. 4A, a blockchain 410 stores a sequence of blocks whichmay be cryptographically linked to each other by storing a hash of aprevious block in a header thereof. However, the example embodimentsfurther introduce the use of a probabilistic filter into a block, whichenables a one-step verification of all blocks in the sequence. In theexample of FIG. 4A, details of a current block 420 are made visible. Inthis example, the current block 420 stores a hash 421 of a previousblock (i−1). In addition, the current block 420 also stores a hash 422of the block content (transactions, etc.) of the current block 420.

According to various embodiments, the current block 420 also includes aprobability filter 423 storing a set of hashes of previous blocks (e.g.,(i−1), (i−2), (i−3), . . . (i−n), etc.) in the sequence of blocks storedon the blockchain 410. A similar probability filter 423 may be stored ineach block of the blockchain 410. The probability filter 423 may includea Bloom filter, or the like, which may be added to the block (e.g.,header, etc.) To generate the bit values stored in the probabilityfilter 423, block hashes of the previous blocks on the blockchain 410may be hashed using a probabilistic hash function. The resulting bitvalues may be stored in a bit array of the probability filter 423. Tosubsequently determine whether a block is included in the probabilisticdata structure, a peer node or other entity may receive the hash of theblock and apply the same probabilistic hash function. The peer node maythen compare the resulting bit value to the bit array to verify the bitsare present in the bit array of the probability filter 423.

To generate the probability filter 423 for the current block 420 whichis represented as block i, a node can use the probability filter of aprevious block (i−1) and accumulate a probabilistic hash of the previousblock (i−1) into the probability filter of the previous block (i−1) togenerate the probability filter 423 of the current block 420 (i.e.,block (i)). As further described with respect to FIG. 4C, the currentblock 420 may also include probability filter 424 which storesprobabilistic hashes of the transactions in the current block 420.Therefore, the block-based probability filter 423 and thetransaction-based probability filter 424 provide a probabilisticverification to demonstrate that a block belongs to an actual sequenceof blocks and also that a transaction belongs to a given block,respectively.

In this example, the probability filter 423 is described as a Bloomfilter, however, different probability filters could also be used suchas a Cuckoo filter, or the like. Regardless of the filter that is used,the idea is not to store all the hashes of each previous block in acurrent block but rather store a compacted representation of the otherblocks. The probability filter 423 stores a hash of each of the blockslike a rolling singular value that accumulates a value of each previousblock in the chain, and can verify each of the previous blocks. Insteadof using the intermediate blocks to validate the whole chain, the systemcan just use a probability filter from one block and verify that a hashof the old block is included in the list of hashes in the probabilityfilter. The probability filter 423 is essentially a list of hashes butit is less data.

To generate a probability filter for a current block, the system may usea previous probability filter from an immediately previous block and addthe probabilistic hash of the previous block to the probability filter.

FIG. 4B illustrates a process 430 of verifying a previous block is partof a sequence of blocks based on the probabilistic filter 423 shown inFIG. 4A, according to example embodiments. In the example of FIG. 4B,the probabilistic filter 423 is stored in a header of a current block(i) and it can be used to perform a one-step verification of anon-consecutive block in the sequence, e.g., block (i−50). It shouldalso be appreciated that the verification does not need to be performedusing a current/most recent block, but rather any block in the sequencethat comes after the block to be verified can be used (including theprobabilistic filter stored therein). In addition, it should beappreciated that the probabilistic data structure may be stored in adata section of the data block instead of being stored in the header.Here, the header may include a digest of the probabilistic datastructure stored in the data section. The digest may provide asummarized or simplified representation of the probabilistic datastructure, or simply an identifier that the data section includes theprobabilistic data structure.

A blockchain peer node 435 may retrieve the probabilistic filter 423from the current block (i) and use the contents therein to verify ablock hash 432 received from a previous block (i−50) to be verified. Inthis example, the block hash 432 is a string value(56ty44409oplkjuHkggksiuekfi41948) which includes numbers and lettersresulting from a hash of block content. The peer node 435 may run aprobabilistic hash function on the string value of the block hash 432 togenerate a probabilistic hash 434. Here, the resulting probabilistichash only has two bit values, in comparison to the lengthy string valueof the block hash 432. To verify that the previous block (i−50) is apart of the sequence, the peer node may verify that the bit values ofthe probabilistic hash 434 are present in the bit values of theprobability data structure of the probability filter 423. In this case,both bit values are present. Accordingly, the peer node 435 maydetermine that it is highly likely that the block (i−50) is a validblock in the sequence of blocks on the blockchain.

An error probability may also be determined based on various factorsincluding the possibility of the bit values present in the probabilityfilter being the result of another hash value. The error probability canbe reduced by increasing the size of the bit array. Also, to reduce asize of the bit array of the probability filter 423, the bit array canbe hashed as well.

FIG. 4C illustrates the probability filter 424 for verifyingtransactions in a block 440 according to example embodiments. Referringto FIG. 4C, the probability filter 424 stores probabilistic hashes ofall transactions in the current block 440. Here, the transactions may bestored in a data section 444 of the block 440. Each transaction may behashed and then probabilistically hashed using a probabilistic hashfunction. The resulting bit values of the probabilistic hash may bestored in the probability filter 424. Meanwhile, the probability filter424 may be stored in a header section 442 of the block 440.

To verify that a transaction is included in the block 440, a peer nodeor other system may retrieve the probability filter 424 from the header442. Next, the peer node may generate a probabilistic hash of thetransaction and compare the probabilistic hash to the bit values in theprobability filter 424 to determine if it is included therein.

FIG. 4D illustrates a process 460 of verifying a document based on aprobabilistic filter according to example embodiments. The process 460corresponds to a verification method that may be performed offline, andmay be complementary to the blockchain verification embodiment describedherein. In the example of FIG. 4D, a probabilistic data structure suchas a Bloom filter, etc., may be graphically encoded within a quickresponse (QR) code and added (printed, copied, etc.) onto a documentsuch as a paper document, a digital document, or the like. Here, theprobabilistic data structure can be used to verify that a document islinked to another document using QR codes and a probabilistic datastructure that includes a rolling value that accumulates a hash of eachdocument in the chain.

In this example, a user device 490 may include an imaging element suchas a camera that is capable of scanning/imaging a QR code 481 from a newdocument 480 and a QR code 471 from a previous document. The user device490 may include software such as a mobile application installed thereinwhich is capable of verifying that the documents 470 and 480 are linkedbased on the scanned data. Here, the user device 490 can verify that theprevious document 470 was indeed created before the new document 480 byretrieving a document hash 472 of the previous document 470 from the QRcode 471 and determining that a probabilistic hash of the document hash472 of the previous document 470 is encompassed by a probabilistic datastructure 483 embedded in the QR code 481 of the new document 480.

As described herein, a QR code may be a graphical representation of ablock header in the previous embodiment. The QR code graphicallyrepresents the probabilistic filter. The hashes in this case may becreated of the document itself. For example, when a file is exportedinto a pdf, the PDF software may offer the ability to convert thedocument into a hash/verifiable format which automatically calculates ahash of the document. The example embodiments may perform a similarprocess and then generate a probabilistic hash of the document hash andstore it in a probabilistic data structure that is embedded within a QRcode.

Referring again to FIG. 4D, the user device 480 may verify the previousdocument 470 based on a document hash 472 stored in the QR code 471 ofthe previous document 470. In this example, the user device 490 may readthe QR code 481 and retrieve embedded content 482 which includes adocument hash of the new document 480, a probabilistic filter 483including an accumulation of document hashes from previous documents, anaccumulative hash, and a signature. The user device 490 may verify thatthe document hash 472 of the previous document 470 is included in theprobabilistic filter 483 of the new document 480. When the verificationis successful, the user device 490 may know that the two documents 470and 480 are linked to each other, and that the previous document 470comes before the new document 480.

FIG. 5A illustrates a method 510 of verifying a block is included in asequence of blocks according to example embodiments. For example, themethod may be performed by a peer node. Referring to FIG. 5A, in 511,the method may include storing a data block that is included within asequential chain of data blocks and which comprises a probabilistic datastructure stored therein. Here, the data block may be stored on ablockchain ledger. In 512, the method may include receiving a request toverify another data block, for example, another data block that ispreviously stored on the blockchain ledger. In 513, the method mayinclude determining whether a probabilistic hash of the other data blockis included within the probabilistic data structure of the stored datablock. In response to a determination that the hash of the other datablock is included within the probabilistic data structure, in 514 themethod may include storing an indicator that the other data block isincluded within the sequential chain of data blocks. The indicator maybe a flag or other value which signifies the verification of the block.As another example, the method may include outputting a notification toa user device, a software application, or other system indicating theblock has been verified.

In some embodiments, the probabilistic data structure may include a bitvector that stores bit values resulting from a hash function beingapplied to data blocks included in the sequential chain of data blocks.In some embodiments, the probabilistic data structure may be storedwithin a header of the stored data block. In some embodiments, the otherdata block may be a non-consecutive data block on the blockchain ledgerwith respect to the stored data block. In other words, one or moreblocks may be between the other data block being verified and the blockwith the probabilistic data structure used for the verifying.

In some embodiments, the determining may include generating theprobabilistic hash of the other data block and comparing bit values ofthe generated probabilistic hash to bit values in the probabilistic datastructure to determine whether the bit values are included in theprobabilistic data structure. In some embodiments, the method mayfurther include generating a probabilistic hash of a hash of the storeddata block and updating the probabilistic data structure to include bitvalues of the generated probabilistic hash. In some embodiments, themethod may further include receiving a request to store a new data blockon the sequential chain of data blocks, and inserting the updatedprobabilistic data structure into a header of the new data block priorto storing the new data block. In some embodiments, the probabilisticdata structure may include an accumulation of bit values generated byapplying a probabilistic hash to hashes of blocks included in thesequential chain of data blocks.

FIG. 5B illustrates a method 520 of verifying a transaction is includedin a block according to example embodiments. For example, the method maybe performed by a peer node. In 521, the method may include storing adata block that is included within a sequential chain of data blocks andwhich comprises a probabilistic data structure stored therein. In 522,the method may include receiving a request to verify a transaction isincluded in the data block. In 523, the method may include determiningwhether a probabilistic hash of the transaction is included within theprobabilistic data structure of the data block. In response to adetermination that the probabilistic hash of the transaction is includedwithin the probabilistic data structure of the data block, in 524 themethod may include storing an indicator that the transaction is includedwithin the data block. Here, the indicator may be a tag or otherindicator which indicates the transaction has been verified. As anotherexample, the method may include outputting a notification to a userdevice, a software application, or other system indicating thetransaction has been verified.

In some embodiments, the determining may include generating theprobabilistic hash of the transaction based on a probabilistic hashfunction, and determining whether bit value of the generatedprobabilistic hash are included in bit values of the probabilistic datastructure. In some embodiments, the probabilistic data structure mayinclude a bit vector that stores bit values resulting from a hashfunction being applied to transactions included in the data block. Insome embodiments, the probabilistic data structure may be stored withina header of the data block.

FIG. 5C illustrates a method 530 of verifying a document is linked toanother document according to example embodiments. For example, themethod 530 may be performed by a user device or other imaging/readingdevice capable of scanning a QR code. In 531, the method may includeobtaining a machine-readable code from a first document among a set ofdocuments. Here, the machine-readable code may be a QR code, a bar code,etc. In 532, the method may include extracting a probabilistic datastructure from the machine-readable code which includes probabilistichashes accumulated from the set of documents. In 533, the method mayinclude determining whether a document hash of a second document isincluded within the probabilistic data structure. In response to adetermination that the document hash is included within theprobabilistic data structure, in 534 the method may include outputting anotification indicating the second document is included in the set ofdocuments.

In some embodiments, the obtaining may include capturing an image of themachine-readable code from a physical document via an imaging element.In some embodiments, the obtaining may include reading themachine-readable code from a digital document stored on a computingdevice. In some embodiments, the probabilistic data structure mayinclude a bit vector that accumulates bit values resulting from a hashfunction being applied to document hashes included in the set ofdocuments. In some embodiments, the determining may include generating aprobabilistic hash of the document hash of the second document, anddetermining whether bit values resulting from the generatedprobabilistic hash are included in the bit vector of the probabilisticdata structure.

In some embodiments, the method may further include generating aprobabilistic hash of a hash of the first document and updating theprobabilistic data structure to include bit values of the generatedprobabilistic hash of the first document. In some embodiments, themethod may further include accumulating the updated probabilistic hashwith the probabilistic data structure, and embedding the accumulatedprobabilistic data structure in a new document in the set of documents.

FIG. 6A illustrates an example system 600 that includes a physicalinfrastructure 610 configured to perform various operations according toexample embodiments. Referring to FIG. 6A, the physical infrastructure610 includes a module 612 and a module 614. The module 614 includes ablockchain 620 and a smart contract 630 (which may reside on theblockchain 620), that may execute any of the operational steps 608 (inmodule 612) included in any of the example embodiments. Thesteps/operations 608 may include one or more of the embodimentsdescribed or depicted and may represent output or written informationthat is written or read from one or more smart contracts 630 and/orblockchains 620. The physical infrastructure 610, the module 612, andthe module 614 may include one or more computers, servers, processors,memories, and/or wireless communication devices. Further, the module 612and the module 614 may be a same module.

FIG. 6B illustrates another example system 640 configured to performvarious operations according to example embodiments. Referring to FIG.6B, the system 640 includes a module 612 and a module 614. The module614 includes a blockchain 620 and a smart contract 630 (which may resideon the blockchain 620), that may execute any of the operational steps608 (in module 612) included in any of the example embodiments. Thesteps/operations 608 may include one or more of the embodimentsdescribed or depicted and may represent output or written informationthat is written or read from one or more smart contracts 630 and/orblockchains 620. The physical infrastructure 610, the module 612, andthe module 614 may include one or more computers, servers, processors,memories, and/or wireless communication devices. Further, the module 612and the module 614 may be a same module.

FIG. 6C illustrates an example system configured to utilize a smartcontract configuration among contracting parties and a mediating serverconfigured to enforce the smart contract terms on the blockchainaccording to example embodiments. Referring to FIG. 6C, theconfiguration 650 may represent a communication session, an assettransfer session or a process or procedure that is driven by a smartcontract 630 which explicitly identifies one or more user devices 652and/or 656. The execution, operations and results of the smart contractexecution may be managed by a server 654. Content of the smart contract630 may require digital signatures by one or more of the entities 652and 656 which are parties to the smart contract transaction. The resultsof the smart contract execution may be written to a blockchain 620 as ablockchain transaction. The smart contract 630 resides on the blockchain620 which may reside on one or more computers, servers, processors,memories, and/or wireless communication devices.

FIG. 6D illustrates a system 660 including a blockchain, according toexample embodiments. Referring to the example of FIG. 6D, an applicationprogramming interface (API) gateway 662 provides a common interface foraccessing blockchain logic (e.g., smart contract 630 or other chaincode)and data (e.g., distributed ledger, etc.). In this example, the APIgateway 662 is a common interface for performing transactions (invoke,queries, etc.) on the blockchain by connecting one or more entities 652and 656 to a blockchain peer (i.e., server 654). Here, the server 654 isa blockchain network peer component that holds a copy of the world stateand a distributed ledger allowing clients 652 and 656 to query data onthe world state as well as submit transactions into the blockchainnetwork where, depending on the smart contract 630 and endorsementpolicy, endorsing peers will run the smart contracts 630.

The above embodiments may be implemented in hardware, in a computerprogram executed by a processor, in firmware, or in a combination of theabove. A computer program may be embodied on a computer readable medium,such as a storage medium. For example, a computer program may reside inrandom access memory (“RAM”), flash memory, read-only memory (“ROM”),erasable programmable read-only memory (“EPROM”), electrically erasableprogrammable read-only memory (“EEPROM”), registers, hard disk, aremovable disk, a compact disk read-only memory (“CD-ROM”), or any otherform of storage medium known in the art.

An exemplary storage medium may be coupled to the processor such thatthe processor may read information from, and write information to, thestorage medium. In the alternative, the storage medium may be integralto the processor. The processor and the storage medium may reside in anapplication specific integrated circuit (“ASIC”). In the alternative,the processor and the storage medium may reside as discrete components.

FIG. 7A illustrates a process 700 of a new block being added to adistributed ledger 720, according to example embodiments, and FIG. 7Billustrates contents of a new data block structure 730 for blockchain,according to example embodiments. Referring to FIG. 7A, clients (notshown) may submit transactions to blockchain nodes 711, 712, and/or 713.Clients may be instructions received from any source to enact activityon the blockchain 720. As an example, clients may be applications thatact on behalf of a requester, such as a device, person or entity topropose transactions for the blockchain. The plurality of blockchainpeers (e.g., blockchain nodes 711, 712, and 713) may maintain a state ofthe blockchain network and a copy of the distributed ledger 720.Different types of blockchain nodes/peers may be present in theblockchain network including endorsing peers which simulate and endorsetransactions proposed by clients and committing peers which verifyendorsements, validate transactions, and commit transactions to thedistributed ledger 720. In this example, the blockchain nodes 711, 712,and 713 may perform the role of endorser node, committer node, or both.

The distributed ledger 720 includes a blockchain which stores immutable,sequenced records in blocks, and a state database 724 (current worldstate) maintaining a current state of the blockchain 722. Onedistributed ledger 720 may exist per channel and each peer maintains itsown copy of the distributed ledger 720 for each channel of which theyare a member. The blockchain 722 is a transaction log, structured ashash-linked blocks where each block contains a sequence of Ntransactions. Blocks may include various components such as shown inFIG. 7B. The linking of the blocks (shown by arrows in FIG. 7A) may begenerated by adding a hash of a prior block's header within a blockheader of a current block. In this way, all transactions on theblockchain 722 are sequenced and cryptographically linked togetherpreventing tampering with blockchain data without breaking the hashlinks. Furthermore, because of the links, the latest block in theblockchain 722 represents every transaction that has come before it. Theblockchain 722 may be stored on a peer file system (local or attachedstorage), which supports an append-only blockchain workload.

The current state of the blockchain 722 and the distributed ledger 722may be stored in the state database 724. Here, the current state datarepresents the latest values for all keys ever included in the chaintransaction log of the blockchain 722. Chaincode invocations executetransactions against the current state in the state database 724. Tomake these chaincode interactions extremely efficient, the latest valuesof all keys are stored in the state database 724. The state database 724may include an indexed view into the transaction log of the blockchain722, it can therefore be regenerated from the chain at any time. Thestate database 724 may automatically get recovered (or generated ifneeded) upon peer startup, before transactions are accepted.

Endorsing nodes receive transactions from clients and endorse thetransaction based on simulated results. Endorsing nodes hold smartcontracts which simulate the transaction proposals. When an endorsingnode endorses a transaction, the endorsing nodes creates a transactionendorsement which is a signed response from the endorsing node to theclient application indicating the endorsement of the simulatedtransaction. The method of endorsing a transaction depends on anendorsement policy which may be specified within chaincode. An exampleof an endorsement policy is “the majority of endorsing peers mustendorse the transaction”. Different channels may have differentendorsement policies. Endorsed transactions are forward by the clientapplication to ordering service 710.

The ordering service 710 accepts endorsed transactions, orders them intoa block, and delivers the blocks to the committing peers. For example,the ordering service 710 may initiate a new block when a threshold oftransactions has been reached, a timer times out, or another condition.In the example of FIG. 7A, blockchain node 712 is a committing peer thathas received a new data new data block 730 for storage on blockchain720. The first block in the blockchain may be referred to as a genesisblock which includes information about the blockchain, its members, thedata stored therein, etc.

The ordering service 710 may be made up of a cluster of orderers. Theordering service 710 does not process transactions, smart contracts, ormaintain the shared ledger. Rather, the ordering service 710 may acceptthe endorsed transactions and specifies the order in which thosetransactions are committed to the distributed ledger 720. Thearchitecture of the blockchain network may be designed such that thespecific implementation of ‘ordering’ (e.g., Solo, Kafka, BFT, etc.)becomes a pluggable component.

Transactions are written to the distributed ledger 720 in a consistentorder. The order of transactions is established to ensure that theupdates to the state database 724 are valid when they are committed tothe network. Unlike a cryptocurrency blockchain system (e.g., Bitcoin,etc.) where ordering occurs through the solving of a cryptographicpuzzle, or mining, in this example the parties of the distributed ledger720 may choose the ordering mechanism that best suits that network.

When the ordering service 710 initializes a new data block 730, the newdata block 730 may be broadcast to committing peers (e.g., blockchainnodes 711, 712, and 713). In response, each committing peer validatesthe transaction within the new data block 730 by checking to make surethat the read set and the write set still match the current world statein the state database 724. Specifically, the committing peer candetermine whether the read data that existed when the endorserssimulated the transaction is identical to the current world state in thestate database 724. When the committing peer validates the transaction,the transaction is written to the blockchain 722 on the distributedledger 720, and the state database 724 is updated with the write datafrom the read-write set. If a transaction fails, that is, if thecommitting peer finds that the read-write set does not match the currentworld state in the state database 724, the transaction ordered into ablock will still be included in that block, but it will be marked asinvalid, and the state database 724 will not be updated.

Referring to FIG. 7B, a new data block 730 (also referred to as a datablock) that is stored on the blockchain 722 of the distributed ledger720 may include multiple data segments such as a block header 740, blockdata 750, and block metadata 760. It should be appreciated that thevarious depicted blocks and their contents, such as new data block 730and its contents. shown in FIG. 7B are merely examples and are not meantto limit the scope of the example embodiments. The new data block 730may store transactional information of N transaction(s) (e.g., 1, 10,100, 500, 1000, 2000, 3000, etc.) within the block data 750. The newdata block 730 may also include a link to a previous block (e.g., on theblockchain 722 in FIG. 7A) within the block header 740. In particular,the block header 740 may include a hash of a previous block's header.The block header 740 may also include a unique block number, a hash ofthe block data 750 of the new data block 730, and the like. The blocknumber of the new data block 730 may be unique and assigned in variousorders, such as an incremental/sequential order starting from zero.

According to various embodiments, the new data block 730 may store oneor more probabilistic filters, for example, an accumulative filter 742for verifying other prior blocks on a blockchain, and a transactionfilter 744 for verifying transactions in the new data block 730. In thisexample, the accumulative filter 742 and the transaction filter 744 arestored in the block header 740, however, embodiments are not limitedthereto. As another example, the probabilistic filters may be stored inthe block data 750 and/or the metadata 760.

The block data 750 may store transactional information of eachtransaction that is recorded within the new data block 730. For example,the transaction data may include one or more of a type of thetransaction, a version, a timestamp, a channel ID of the distributedledger 720, a transaction ID, an epoch, a payload visibility, achaincode path (deploy tx), a chaincode name, a chaincode version, input(chaincode and functions), a client (creator) identify such as a publickey and certificate, a signature of the client, identities of endorsers,endorser signatures, a proposal hash, chaincode events, response status,namespace, a read set (list of key and version read by the transaction,etc.), a write set (list of key and value, etc.), a start key, an endkey, a list of keys, a Merkel tree query summary, and the like. Thetransaction data may be stored for each of the N transactions.

The block metadata 760 may store multiple fields of metadata (e.g., as abyte array, etc.). Metadata fields may include signature on blockcreation, a reference to a last configuration block, a transactionfilter identifying valid and invalid transactions within the block, lastoffset persisted of an ordering service that ordered the block, and thelike. The signature, the last configuration block, and the orderermetadata may be added by the ordering service 710. Meanwhile, acommitter of the block (such as blockchain node 712) may addvalidity/invalidity information based on an endorsement policy,verification of read/write sets, and the like. The transaction filtermay include a byte array of a size equal to the number of transactionsin the block data 750 and a validation code identifying whether atransaction was valid/invalid.

FIG. 7C illustrates an embodiment of a blockchain 770 for digitalcontent in accordance with the embodiments described herein. The digitalcontent may include one or more files and associated information. Thefiles may include media, images, video, audio, text, links, graphics,animations, web pages, documents, or other forms of digital content. Theimmutable, append-only aspects of the blockchain serve as a safeguard toprotect the integrity, validity, and authenticity of the digitalcontent, making it suitable use in legal proceedings where admissibilityrules apply or other settings where evidence is taken in toconsideration or where the presentation and use of digital informationis otherwise of interest. In this case, the digital content may bereferred to as digital evidence.

The blockchain may be formed in various ways. In one embodiment, thedigital content may be included in and accessed from the blockchainitself. For example, each block of the blockchain may store a hash valueof reference information (e.g., header, value, etc.) along theassociated digital content. The hash value and associated digitalcontent may then be encrypted together. Thus, the digital content ofeach block may be accessed by decrypting each block in the blockchain,and the hash value of each block may be used as a basis to reference aprevious block. This may be illustrated as follows:

Block 1 Block 2 . . . Block N Hash Value 1 Hash Value 2 Hash Value NDigital Content 1 Digital Content 2 Digital Content N

In one embodiment, the digital content may be not included in theblockchain. For example, the blockchain may store the encrypted hashesof the content of each block without any of the digital content. Thedigital content may be stored in another storage area or memory addressin association with the hash value of the original file. The otherstorage area may be the same storage device used to store the blockchainor may be a different storage area or even a separate relationaldatabase. The digital content of each block may be referenced oraccessed by obtaining or querying the hash value of a block of interestand then looking up that has value in the storage area, which is storedin correspondence with the actual digital content. This operation may beperformed, for example, a database gatekeeper. This may be illustratedas follows:

Blockchain Storage Area Block 1 Hash Value Block 1 Hash Value . . .Content . . . . . . Block N Hash Value Block N Hash Value . . . Content

In the example embodiment of FIG. 7C, the blockchain 770 includes anumber of blocks 778 ₁, 778 ₂, . . . 778 _(N) cryptographically linkedin an ordered sequence, where N≥1. The encryption used to link theblocks 778 ₁, 778 ₂, . . . 778 _(N) may be any of a number of keyed orun-keyed Hash functions. In one embodiment, the blocks 778 ₁, 778 ₂, . .. 778 _(N) are subject to a hash function which produces n-bitalphanumeric outputs (where n is 256 or another number) from inputs thatare based on information in the blocks. Examples of such a hash functioninclude, but are not limited to, a SHA-type (SHA stands for Secured HashAlgorithm) algorithm, Merkle-Damgard algorithm, HAIFA algorithm,Merkle-tree algorithm, nonce-based algorithm, and anon-collision-resistant PRF algorithm. In another embodiment, the blocks778 ₁, 778 ₂, . . . , 778 _(N) may be cryptographically linked by afunction that is different from a hash function. For purposes ofillustration, the following description is made with reference to a hashfunction, e.g., SHA-2.

Each of the blocks 778 ₁, 778 ₂, . . . , 778 _(N) in the blockchainincludes a header, a version of the file, and a value. The header andthe value are different for each block as a result of hashing in theblockchain. In one embodiment, the value may be included in the header.As described in greater detail below, the version of the file may be theoriginal file or a different version of the original file.

The first block 778 ₁ in the blockchain is referred to as the genesisblock and includes the header 772 ₁, original file 774 ₁, and an initialvalue 776 ₁. The hashing scheme used for the genesis block, and indeedin all subsequent blocks, may vary. For example, all the information inthe first block 778 ₁ may be hashed together and at one time, or each ora portion of the information in the first block 778 ₁ may be separatelyhashed and then a hash of the separately hashed portions may beperformed.

The header 772 ₁ may include one or more initial parameters, which, forexample, may include a version number, timestamp, nonce, rootinformation, difficulty level, consensus protocol, duration, mediaformat, source, descriptive keywords, and/or other informationassociated with original file 774 ₁ and/or the blockchain. The header772 ₁ may be generated automatically (e.g., by blockchain networkmanaging software) or manually by a blockchain participant. Unlike theheader in other blocks 778 ₂ to 778 _(N) in the blockchain, the header772 ₁ in the genesis block does not reference a previous block, simplybecause there is no previous block.

The original file 774 ₁ in the genesis block may be, for example, dataas captured by a device with or without processing prior to itsinclusion in the blockchain. The original file 774 ₁ is received throughthe interface of the system from the device, media source, or node. Theoriginal file 774 ₁ is associated with metadata, which, for example, maybe generated by a user, the device, and/or the system processor, eithermanually or automatically. The metadata may be included in the firstblock 778 ₁ in association with the original file 774 ₁.

The value 776 ₁ in the genesis block is an initial value generated basedon one or more unique attributes of the original file 774 ₁. In oneembodiment, the one or more unique attributes may include the hash valuefor the original file 774 ₁, metadata for the original file 774 ₁, andother information associated with the file. In one implementation, theinitial value 776 ₁ may be based on the following unique attributes:

-   -   1) SHA-2 computed hash value for the original file    -   2) originating device ID    -   3) starting timestamp for the original file    -   4) initial storage location of the original file    -   5) blockchain network member ID for software to currently        control the original file and associated metadata

The other blocks 778 ₂ to 778 _(N) in the blockchain also have headers,files, and values. However, unlike the first block 772 ₁, each of theheaders 772 ₂ to 772 _(N) in the other blocks includes the hash value ofan immediately preceding block. The hash value of the immediatelypreceding block may be just the hash of the header of the previous blockor may be the hash value of the entire previous block. By including thehash value of a preceding block in each of the remaining blocks, a tracecan be performed from the Nth block back to the genesis block (and theassociated original file) on a block-by-block basis, as indicated byarrows 780, to establish an auditable and immutable chain-of-custody.

Each of the header 772 ₂ to 772 _(N) in the other blocks may alsoinclude other information, e.g., version number, timestamp, nonce, rootinformation, difficulty level, consensus protocol, and/or otherparameters or information associated with the corresponding files and/orthe blockchain in general.

The files 774 ₂ to 774 _(N) in the other blocks may be equal to theoriginal file or may be a modified version of the original file in thegenesis block depending, for example, on the type of processingperformed. The type of processing performed may vary from block toblock. The processing may involve, for example, any modification of afile in a preceding block, such as redacting information or otherwisechanging the content of, taking information away from, or adding orappending information to the files.

Additionally, or alternatively, the processing may involve merelycopying the file from a preceding block, changing a storage location ofthe file, analyzing the file from one or more preceding blocks, movingthe file from one storage or memory location to another, or performingaction relative to the file of the blockchain and/or its associatedmetadata. Processing which involves analyzing a file may include, forexample, appending, including, or otherwise associating variousanalytics, statistics, or other information associated with the file.

The values in each of the other blocks 776 ₂ to 776 _(N) in the otherblocks are unique values and are all different as a result of theprocessing performed. For example, the value in any one blockcorresponds to an updated version of the value in the previous block.The update is reflected in the hash of the block to which the value isassigned. The values of the blocks therefore provide an indication ofwhat processing was performed in the blocks and also permit a tracingthrough the blockchain back to the original file. This tracking confirmsthe chain-of-custody of the file throughout the entire blockchain.

For example, consider the case where portions of the file in a previousblock are redacted, blocked out, or pixelated in order to protect theidentity of a person shown in the file. In this case, the blockincluding the redacted file will include metadata associated with theredacted file, e.g., how the redaction was performed, who performed theredaction, timestamps where the redaction(s) occurred, etc. The metadatamay be hashed to form the value. Because the metadata for the block isdifferent from the information that was hashed to form the value in theprevious block, the values are different from one another and may berecovered when decrypted.

In one embodiment, the value of a previous block may be updated (e.g., anew hash value computed) to form the value of a current block when anyone or more of the following occurs. The new hash value may be computedby hashing all or a portion of the information noted below, in thisexample embodiment.

-   -   a) new SHA-2 computed hash value if the file has been processed        in any way (e.g., if the file was redacted, copied, altered,        accessed, or some other action was taken)    -   b) new storage location for the file    -   c) new metadata identified associated with the file    -   d) transfer of access or control of the file from one blockchain        participant to another blockchain participant

FIG. 7D illustrates an embodiment of a block which may represent thestructure of the blocks in the blockchain 790 in accordance with oneembodiment. The block, Block_(i), includes a header 772 _(i), a file 774_(i), and a value 776 _(i).

The header 772 _(i) includes a hash value of a previous blockBlock_(i-1) and additional reference information, which, for example,may be any of the types of information (e.g., header informationincluding references, characteristics, parameters, etc.) discussedherein. All blocks reference the hash of a previous block except, ofcourse, the genesis block. The hash value of the previous block may bejust a hash of the header in the previous block or a hash of all or aportion of the information in the previous block, including the file andmetadata.

The file 774 _(i) includes a plurality of data, such as Data 1, Data 2,. . . , Data N in sequence. The data are tagged with metadata Metadata1, Metadata 2, . . . , Metadata N which describe the content and/orcharacteristics associated with the data. For example, the metadata foreach data may include information to indicate a timestamp for the data,process the data, keywords indicating the persons or other contentdepicted in the data, and/or other features that may be helpful toestablish the validity and content of the file as a whole, andparticularly its use a digital evidence, for example, as described inconnection with an embodiment discussed below. In addition to themetadata, each data may be tagged with reference REF₁, REF₂, . . . ,REF_(N) to a previous data to prevent tampering, gaps in the file, andsequential reference through the file.

Once the metadata is assigned to the data (e.g., through a smartcontract), the metadata cannot be altered without the hash changing,which can easily be identified for invalidation. The metadata, thus,creates a data log of information that may be accessed for use byparticipants in the blockchain.

The value 776 _(i) is a hash value or other value computed based on anyof the types of information previously discussed. For example, for anygiven block Block_(i), the value for that block may be updated toreflect the processing that was performed for that block, e.g., new hashvalue, new storage location, new metadata for the associated file,transfer of control or access, identifier, or other action orinformation to be added. Although the value in each block is shown to beseparate from the metadata for the data of the file and header, thevalue may be based, in part or whole, on this metadata in anotherembodiment.

Once the blockchain 770 is formed, at any point in time, the immutablechain-of-custody for the file may be obtained by querying the blockchainfor the transaction history of the values across the blocks. This query,or tracking procedure, may begin with decrypting the value of the blockthat is most currently included (e.g., the last (N^(th)) block), andthen continuing to decrypt the value of the other blocks until thegenesis block is reached and the original file is recovered. Thedecryption may involve decrypting the headers and files and associatedmetadata at each block, as well.

Decryption is performed based on the type of encryption that took placein each block. This may involve the use of private keys, public keys, ora public key-private key pair. For example, when asymmetric encryptionis used, blockchain participants or a processor in the network maygenerate a public key and private key pair using a predeterminedalgorithm. The public key and private key are associated with each otherthrough some mathematical relationship. The public key may bedistributed publicly to serve as an address to receive messages fromother users, e.g., an IP address or home address. The private key iskept secret and used to digitally sign messages sent to other blockchainparticipants. The signature is included in the message so that therecipient can verify using the public key of the sender. This way, therecipient can be sure that only the sender could have sent this message.

Generating a key pair may be analogous to creating an account on theblockchain, but without having to actually register anywhere. Also,every transaction that is executed on the blockchain is digitally signedby the sender using their private key. This signature ensures that onlythe owner of the account can track and process (if within the scope ofpermission determined by a smart contract) the file of the blockchain.

FIGS. 8A and 8B illustrate additional examples of use cases forblockchain which may be incorporated and used herein. In particular,FIG. 8A illustrates an example 800 of a blockchain 810 which storesmachine learning (artificial intelligence) data. Machine learning relieson vast quantities of historical data (or training data) to buildpredictive models for accurate prediction on new data. Machine learningsoftware (e.g., neural networks, etc.) can often sift through millionsof records to unearth non-intuitive patterns.

In the example of FIG. 8A, a host platform 820 builds and deploys amachine learning model for predictive monitoring of assets 830. Here,the host platform 820 may be a cloud platform, an industrial server, aweb server, a personal computer, a user device, and the like. Assets 830can be any type of asset (e.g., machine or equipment, etc.) such as anaircraft, locomotive, turbine, medical machinery and equipment, oil andgas equipment, boats, ships, vehicles, and the like. As another example,assets 830 may be non-tangible assets such as stocks, currency, digitalcoins, insurance, or the like.

The blockchain 810 can be used to significantly improve both a trainingprocess 802 of the machine learning model and a predictive process 804based on a trained machine learning model. For example, in 802, ratherthan requiring a data scientist/engineer or other user to collect thedata, historical data may be stored by the assets 830 themselves (orthrough an intermediary, not shown) on the blockchain 810. This cansignificantly reduce the collection time needed by the host platform 820when performing predictive model training. For example, using smartcontracts, data can be directly and reliably transferred straight fromits place of origin to the blockchain 810. By using the blockchain 810to ensure the security and ownership of the collected data, smartcontracts may directly send the data from the assets to the individualsthat use the data for building a machine learning model. This allows forsharing of data among the assets 830.

The collected data may be stored in the blockchain 810 based on aconsensus mechanism. The consensus mechanism pulls in (permissionednodes) to ensure that the data being recorded is verified and accurate.The data recorded is time-stamped, cryptographically signed, andimmutable. It is therefore auditable, transparent, and secure. AddingIoT devices which write directly to the blockchain can, in certain cases(i.e. supply chain, healthcare, logistics, etc.), increase both thefrequency and accuracy of the data being recorded.

Furthermore, training of the machine learning model on the collecteddata may take rounds of refinement and testing by the host platform 820.Each round may be based on additional data or data that was notpreviously considered to help expand the knowledge of the machinelearning model. In 802, the different training and testing steps (andthe data associated therewith) may be stored on the blockchain 810 bythe host platform 820. Each refinement of the machine learning model(e.g., changes in variables, weights, etc.) may be stored on theblockchain 810. This provides verifiable proof of how the model wastrained and what data was used to train the model. Furthermore, when thehost platform 820 has achieved a finally trained model, the resultingmodel may be stored on the blockchain 810.

After the model has been trained, it may be deployed to a liveenvironment where it can make predictions/decisions based on theexecution of the final trained machine learning model. For example, in804, the machine learning model may be used for condition-basedmaintenance (CBM) for an asset such as an aircraft, a wind turbine, ahealthcare machine, and the like. In this example, data fed back fromthe asset 830 may be input the machine learning model and used to makeevent predictions such as failure events, error codes, and the like.Determinations made by the execution of the machine learning model atthe host platform 820 may be stored on the blockchain 810 to provideauditable/verifiable proof. As one non-limiting example, the machinelearning model may predict a future breakdown/failure to a part of theasset 830 and create alert or a notification to replace the part. Thedata behind this decision may be stored by the host platform 820 on theblockchain 810. In one embodiment the features and/or the actionsdescribed and/or depicted herein can occur on or with respect to theblockchain 810.

New transactions for a blockchain can be gathered together into a newblock and added to an existing hash value. This is then encrypted tocreate a new hash for the new block. This is added to the next list oftransactions when they are encrypted, and so on. The result is a chainof blocks that each contain the hash values of all preceding blocks.Computers that store these blocks regularly compare their hash values toensure that they are all in agreement. Any computer that does not agree,discards the records that are causing the problem. This approach is goodfor ensuring tamper-resistance of the blockchain, but it is not perfect.

One way to game this system is for a dishonest user to change the listof transactions in their favor, but in a way that leaves the hashunchanged. This can be done by brute force, in other words by changing arecord, encrypting the result, and seeing whether the hash value is thesame. And if not, trying again and again and again until it finds a hashthat matches. The security of blockchains is based on the belief thatordinary computers can only perform this kind of brute force attack overtime scales that are entirely impractical, such as the age of theuniverse. By contrast, quantum computers are much faster (1000s of timesfaster) and consequently pose a much greater threat.

FIG. 8B illustrates an example 850 of a quantum-secure blockchain 852which implements quantum key distribution (QKD) to protect against aquantum computing attack. In this example, blockchain users can verifyeach other's identities using QKD. This sends information using quantumparticles such as photons, which cannot be copied by an eavesdropperwithout destroying them. In this way, a sender and a receiver throughthe blockchain can be sure of each other's identity.

In the example of FIG. 8B, four users are present 854, 856, 858, and860. Each of pair of users may share a secret key 862 (i.e., a QKD)between themselves. Since there are four nodes in this example, sixpairs of nodes exists, and therefore six different secret keys 862 areused including QKD_(AB), QKD_(AC), QKD_(AD), QKD_(BC), QKD_(BD), andQKD_(CD). Each pair can create a QKD by sending information usingquantum particles such as photons, which cannot be copied by aneavesdropper without destroying them. In this way, a pair of users canbe sure of each other's identity.

The operation of the blockchain 852 is based on two procedures (i)creation of transactions, and (ii) construction of blocks that aggregatethe new transactions. New transactions may be created similar to atraditional blockchain network. Each transaction may contain informationabout a sender, a receiver, a time of creation, an amount (or value) tobe transferred, a list of reference transactions that justifies thesender has funds for the operation, and the like. This transactionrecord is then sent to all other nodes where it is entered into a poolof unconfirmed transactions. Here, two parties (i.e., a pair of usersfrom among 854-860) authenticate the transaction by providing theirshared secret key 862 (QKD). This quantum signature can be attached toevery transaction making it exceedingly difficult to tamper with. Eachnode checks their entries with respect to a local copy of the blockchain852 to verify that each transaction has sufficient funds. However, thetransactions are not yet confirmed.

Rather than perform a traditional mining process on the blocks, theblocks may be created in a decentralized manner using a broadcastprotocol. At a predetermined period of time (e.g., seconds, minutes,hours, etc.) the network may apply the broadcast protocol to anyunconfirmed transaction thereby to achieve a Byzantine agreement(consensus) regarding a correct version of the transaction. For example,each node may possess a private value (transaction data of thatparticular node). In a first round, nodes transmit their private valuesto each other. In subsequent rounds, nodes communicate the informationthey received in the previous round from other nodes. Here, honest nodesare able to create a complete set of transactions within a new block.This new block can be added to the blockchain 852. In one embodiment thefeatures and/or the actions described and/or depicted herein can occuron or with respect to the blockchain 852.

FIG. 9 illustrates an example system 900 that supports one or more ofthe example embodiments described and/or depicted herein. The system 900comprises a computer system/server 902, which is operational withnumerous other general purpose or special purpose computing systemenvironments or configurations. Examples of well-known computingsystems, environments, and/or configurations that may be suitable foruse with computer system/server 902 include, but are not limited to,personal computer systems, server computer systems, thin clients, thickclients, hand-held or laptop devices, multiprocessor systems,microprocessor-based systems, set top boxes, programmable consumerelectronics, network PCs, minicomputer systems, mainframe computersystems, and distributed cloud computing environments that include anyof the above systems or devices, and the like.

Computer system/server 902 may be described in the general context ofcomputer system-executable instructions, such as program modules, beingexecuted by a computer system. Generally, program modules may includeroutines, programs, objects, components, logic, data structures, and soon that perform particular tasks or implement particular abstract datatypes. Computer system/server 902 may be practiced in distributed cloudcomputing environments where tasks are performed by remote processingdevices that are linked through a communications network. In adistributed cloud computing environment, program modules may be locatedin both local and remote computer system storage media including memorystorage devices.

As shown in FIG. 9, computer system/server 902 in cloud computing node900 is shown in the form of a general-purpose computing device. Thecomponents of computer system/server 902 may include, but are notlimited to, one or more processors or processing units 904, a systemmemory 906, and a bus that couples various system components includingsystem memory 906 to processor 904.

The bus represents one or more of any of several types of busstructures, including a memory bus or memory controller, a peripheralbus, an accelerated graphics port, and a processor or local bus usingany of a variety of bus architectures. By way of example, and notlimitation, such architectures include Industry Standard Architecture(ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA)bus, Video Electronics Standards Association (VESA) local bus, andPeripheral Component Interconnects (PCI) bus.

Computer system/server 902 typically includes a variety of computersystem readable media. Such media may be any available media that isaccessible by computer system/server 902, and it includes both volatileand non-volatile media, removable and non-removable media. System memory906, in one embodiment, implements the flow diagrams of the otherfigures. The system memory 906 can include computer system readablemedia in the form of volatile memory, such as random-access memory (RAM)910 and/or cache memory 912. Computer system/server 902 may furtherinclude other removable/non-removable, volatile/non-volatile computersystem storage media. By way of example only, storage system 914 can beprovided for reading from and writing to a non-removable, non-volatilemagnetic media (not shown and typically called a “hard drive”). Althoughnot shown, a magnetic disk drive for reading from and writing to aremovable, non-volatile magnetic disk (e.g., a “floppy disk”), and anoptical disk drive for reading from or writing to a removable,non-volatile optical disk such as a CD-ROM, DVD-ROM or other opticalmedia can be provided. In such instances, each can be connected to thebus by one or more data media interfaces. As will be further depictedand described below, memory 906 may include at least one program producthaving a set (e.g., at least one) of program modules that are configuredto carry out the functions of various embodiments of the application.

Program/utility 916, having a set (at least one) of program modules 918,may be stored in memory 906 by way of example, and not limitation, aswell as an operating system, one or more application programs, otherprogram modules, and program data. Each of the operating system, one ormore application programs, other program modules, and program data orsome combination thereof, may include an implementation of a networkingenvironment. Program modules 918 generally carry out the functionsand/or methodologies of various embodiments of the application asdescribed herein.

As will be appreciated by one skilled in the art, aspects of the presentapplication may be embodied as a system, method, or computer programproduct. Accordingly, aspects of the present application may take theform of an entirely hardware embodiment, an entirely software embodiment(including firmware, resident software, micro-code, etc.) or anembodiment combining software and hardware aspects that may allgenerally be referred to herein as a “circuit,” “module” or “system.”Furthermore, aspects of the present application may take the form of acomputer program product embodied in one or more computer readablemedium(s) having computer readable program code embodied thereon.

Computer system/server 902 may also communicate with one or moreexternal devices 920 such as a keyboard, a pointing device, a display922, etc.; one or more devices that enable a user to interact withcomputer system/server 902; and/or any devices (e.g., network card,modem, etc.) that enable computer system/server 902 to communicate withone or more other computing devices. Such communication can occur viaI/O interfaces 924. Still yet, computer system/server 902 cancommunicate with one or more networks such as a local area network(LAN), a general wide area network (WAN), and/or a public network (e.g.,the Internet) via network adapter 926. As depicted, network adapter 926communicates with the other components of computer system/server 902 viaa bus. It should be understood that although not shown, other hardwareand/or software components could be used in conjunction with computersystem/server 902. Examples, include, but are not limited to: microcode,device drivers, redundant processing units, external disk drive arrays,RAID systems, tape drives, and data archival storage systems, etc.

Although an exemplary embodiment of at least one of a system, method,and non-transitory computer readable medium has been illustrated in theaccompanied drawings and described in the foregoing detaileddescription, it will be understood that the application is not limitedto the embodiments disclosed, but is capable of numerous rearrangements,modifications, and substitutions as set forth and defined by thefollowing claims. For example, the capabilities of the system of thevarious figures can be performed by one or more of the modules orcomponents described herein or in a distributed architecture and mayinclude a transmitter, receiver or pair of both. For example, all orpart of the functionality performed by the individual modules, may beperformed by one or more of these modules. Further, the functionalitydescribed herein may be performed at various times and in relation tovarious events, internal or external to the modules or components. Also,the information sent between various modules can be sent between themodules via at least one of: a data network, the Internet, a voicenetwork, an Internet Protocol network, a wireless device, a wired deviceand/or via plurality of protocols. Also, the messages sent or receivedby any of the modules may be sent or received directly and/or via one ormore of the other modules.

One skilled in the art will appreciate that a “system” could be embodiedas a personal computer, a server, a console, a personal digitalassistant (PDA), a cell phone, a tablet computing device, a smartphoneor any other suitable computing device, or combination of devices.Presenting the above-described functions as being performed by a“system” is not intended to limit the scope of the present applicationin any way but is intended to provide one example of many embodiments.Indeed, methods, systems and apparatuses disclosed herein may beimplemented in localized and distributed forms consistent with computingtechnology.

It should be noted that some of the system features described in thisspecification have been presented as modules, in order to moreparticularly emphasize their implementation independence. For example, amodule may be implemented as a hardware circuit comprising custom verylarge-scale integration (VLSI) circuits or gate arrays, off-the-shelfsemiconductors such as logic chips, transistors, or other discretecomponents. A module may also be implemented in programmable hardwaredevices such as field programmable gate arrays, programmable arraylogic, programmable logic devices, graphics processing units, or thelike.

A module may also be at least partially implemented in software forexecution by various types of processors. An identified unit ofexecutable code may, for instance, comprise one or more physical orlogical blocks of computer instructions that may, for instance, beorganized as an object, procedure, or function. Nevertheless, theexecutables of an identified module need not be physically locatedtogether but may comprise disparate instructions stored in differentlocations which, when joined logically together, comprise the module andachieve the stated purpose for the module. Further, modules may bestored on a computer-readable medium, which may be, for instance, a harddisk drive, flash device, random access memory (RAM), tape, or any othersuch medium used to store data.

Indeed, a module of executable code could be a single instruction, ormany instructions, and may even be distributed over several differentcode segments, among different programs, and across several memorydevices. Similarly, operational data may be identified and illustratedherein within modules and may be embodied in any suitable form andorganized within any suitable type of data structure. The operationaldata may be collected as a single data set or may be distributed overdifferent locations including over different storage devices, and mayexist, at least partially, merely as electronic signals on a system ornetwork.

It will be readily understood that the components of the application, asgenerally described and illustrated in the figures herein, may bearranged and designed in a wide variety of different configurations.Thus, the detailed description of the embodiments is not intended tolimit the scope of the application as claimed but is merelyrepresentative of selected embodiments of the application.

One having ordinary skill in the art will readily understand that theabove may be practiced with steps in a different order, and/or withhardware elements in configurations that are different than those whichare disclosed. Therefore, although the application has been describedbased upon these preferred embodiments, it would be apparent to those ofskill in the art that certain modifications, variations, and alternativeconstructions would be apparent.

While preferred embodiments of the present application have beendescribed, it is to be understood that the embodiments described areillustrative only and the scope of the application is to be definedsolely by the appended claims when considered with a full range ofequivalents and modifications (e.g., protocols, hardware devices,software platforms etc.) thereto.

What is claimed is:
 1. An apparatus comprising: a processor configuredto obtain a machine-readable code from a first document among a set ofdocuments, extract a probabilistic data structure from themachine-readable code which includes probabilistic hashes accumulatedfrom the set of documents, and determine whether a document hash of asecond document is included within the probabilistic data structure; anda display configured to output a notification that indicates the seconddocument is included in the set of documents, in response to adetermination that the document hash is included within theprobabilistic data structure.
 2. The apparatus of claim 1, wherein themachine-readable code comprises a quick response (QR) code with theprobabilistic data structure embedded therein.
 3. The apparatus of claim1, wherein the processor is configured to capture an image of themachine-readable code from a physical document via an imaging element.4. The apparatus of claim 1, wherein the processor is configured to readthe machine-readable code from a digital document stored on a computingdevice.
 5. The apparatus of claim 1, wherein the probabilistic datastructure comprises a bit vector that accumulates bit values that resultfrom a hash function that is applied to document hashes included in theset of documents.
 6. The apparatus of claim 5, wherein the processor isconfigured to generate a probabilistic hash of the document hash of thesecond document, and determine whether bit values that result from thegenerated probabilistic hash are included in the bit vector of theprobabilistic data structure.
 7. The apparatus of claim 1, wherein theprocessor is configured to generate a probabilistic hash of a hash ofthe first document and update the probabilistic data structure toinclude bit values of the generated probabilistic hash of the firstdocument.
 8. The apparatus of claim 7, wherein the processor is furtherconfigured to accumulate the updated probabilistic hash with theprobabilistic data structure, and embed the accumulated probabilisticdata structure in a new document in the set of documents.
 9. A methodcomprising: obtaining a machine-readable code from a first documentamong a set of documents; extracting a probabilistic data structure fromthe machine-readable code which includes probabilistic hashesaccumulated from the set of documents; determining whether a documenthash of a second document is included within the probabilistic datastructure; and in response to a determination that the document hash isincluded within the probabilistic data structure, outputting anotification indicating the second document is included in the set ofdocuments.
 10. The method of claim 9, wherein the machine-readable codecomprises a quick response (QR) code with the probabilistic datastructure embedded therein.
 11. The method of claim 9, wherein theobtaining comprises capturing an image of the machine-readable code froma physical document via an imaging element.
 12. The method of claim 9,wherein the obtaining comprises reading the machine-readable code from adigital document stored on a computing device.
 13. The method of claim9, wherein the probabilistic data structure comprises a bit vector thataccumulates bit values resulting from a hash function being applied todocument hashes included in the set of documents.
 14. The method ofclaim 13, wherein the determining comprises generating a probabilistichash of the document hash of the second document, and determiningwhether bit values resulting from the generated probabilistic hash areincluded in the bit vector of the probabilistic data structure.
 15. Themethod of claim 9, further comprising generating a probabilistic hash ofa hash of the first document and updating the probabilistic datastructure to include bit values of the generated probabilistic hash ofthe first document.
 16. The method of claim 15, further comprisingaccumulating the updated probabilistic hash with the probabilistic datastructure, and embedding the accumulated probabilistic data structure ina new document in the set of documents.
 17. A non-transitorycomputer-readable medium comprising instructions, that when read by aprocessor, cause the processor to perform a method comprising: obtaininga machine-readable code from a first document among a set of documents;extracting a probabilistic data structure from the machine-readable codewhich includes probabilistic hashes accumulated from the set ofdocuments; determining whether a document hash of a second document isincluded within the probabilistic data structure; and in response to adetermination that the document hash is included within theprobabilistic data structure, outputting a notification indicating thesecond document is included in the set of documents.
 18. Anon-transitory computer-readable medium of claim 17, wherein themachine-readable code comprises a quick response (QR) code with theprobabilistic data structure embedded therein.
 19. A non-transitorycomputer-readable medium of claim 17, wherein the probabilistic datastructure comprises a bit vector that accumulates bit values resultingfrom a hash function being applied to document hashes included in theset of documents.
 20. The non-transitory computer-readable medium ofclaim 19, wherein the determining comprises generating a probabilistichash of the document hash of the second document, and determiningwhether bit values resulting from the generated probabilistic hash areincluded in the bit vector of the probabilistic data structure.